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bvartools (version 0.0.3)

Bayesian Inference of Vector Autoregressive Models

Description

Assists in the set-up of algorithms for Bayesian inference of vector autoregressive (VAR) models. Functions for posterior simulation, forecasting, impulse response analysis and forecast error variance decomposition are largely based on the introductory texts of Koop and Korobilis (2010) and Luetkepohl (2007, ISBN: 9783540262398).

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Install

install.packages('bvartools')

Monthly Downloads

570

Version

0.0.3

License

GPL (>= 2)

Issues

3

Pull Requests

0

Stars

34

Forks

11

Maintainer

Franz X. Mohr

Last Published

July 23rd, 2020

Functions in bvartools (0.0.3)

bvartools

bvartools: Bayesian Inference of Vector Autoregressive Models
e1

West German economic time series data
bvec_to_bvar

Transform a VECM to VAR in levels
gen_vec

Vector Error Correction Model Input
bvec

Bayesian Vector Error Correction Objects
bvs

Bayesian Variable Selection
bvar

Bayesian Vector Autoregression Objects
gen_var

Vector Autoregressive Model Input
fevd

Forecast Error Variance Decomposition
e6

German interest and inflation rate data
post_coint_kls

Posterior Draw for Cointegration Models
kalman_dk

Durbin and Koopman Simulation Smoother
loglik_normal

Calculates the log-likelihood of a multivariate normal distribution.
post_normal

Posterior Draw from a Normal Distribution
summary.bvar

Summarising Bayesian VAR Coefficients
post_normal_sur

Posterior Draw from a Normal Distribution
summary.bvec

Summarising Bayesian VEC Coefficients
minnesota_prior

Minnesota Prior
ssvs

Stochastic Search Variable Selection
plot.bvarprd

Plotting Forecasts of BVAR Models
post_coint_kls_sur

Posterior Draw for Cointegration Models
us_macrodata

US macroeconomic data
thin

Thinning Posterior Draws
inclusion_prior

Prior Inclusion Probabilities
ssvs_prior

Stochastic Search Variable Selection Prior
irf

Impulse Response Function